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Published OnlineFirst February 23, 2010; DOI: 10.1158/1940-6207.CAPR-09-0188 Cancer Prevention Research Research Article Finasteride Modifies the Relation between Serum C-Peptide and Prostate Cancer Risk: Results from the Prostate Cancer Prevention Trial Marian L. Neuhouser1, Cathee Till1, Alan Kristal1,2, Phyllis Goodman1, Ashraful Hoque3, Elizabeth A. Platz4, Ann W. Hsing5, Demetrius Albanes5, Howard L. Parnes6, and Michael Pollak7 Abstract Hyperinsulinemia and obesity-related metabolic disturbances are common and have been associated with increased cancer risk and poor prognosis. To investigate this issue in relation to prostate cancer, we conducted a nested case-control study within the Prostate Cancer Prevention Trial (PCPT), a randomized, placebo-controlled trial testing finasteride versus placebo for primary prevention of prostate cancer. Cases (n = 1,803) and controls (n = 1,797) were matched on age, PCPT treatment arm, and family history of prostate cancer; controls included all eligible non-whites. Baseline bloods were assayed for serum Cpeptide (marker of insulin secretion) and leptin (an adipokine) using ELISA. All outcomes were biopsy determined. Logistic regression calculated odds ratios (OR) for total prostate cancer and polytomous logistic regression calculated ORs for low-grade (Gleason <7) and high-grade (Gleason >7) disease. Results were stratified by PCPT treatment arm for C-peptide. For men on placebo, higher versus lower serum C-peptide was associated with a nearly 2-fold increased risk of high-grade prostate cancer (Gleason >7; multivariate-adjusted OR, 1.88; 95% confidence interval, 1.19–2.97; Ptrend = 0.004). When C-peptide was modeled as a continuous variable, every unit increase in log(C-peptide) resulted in a 39% increased risk of high-grade disease (P = 0.01). In contrast, there was no significant relationship between C-peptide and high-grade prostate cancer among men receiving finasteride. Leptin was not independently associated with high-grade prostate cancer. In conclusion, these results support findings from other observational studies that high serum C-peptide and insulin resistance, but not leptin, are associated with increased risk of high-grade prostate cancer. Our novel finding is that the C-peptide–associated risk was attenuated by use of finasteride. Cancer Prev Res; 3(3); 279–89. ©2010 AACR. Introduction Metabolic dysfunction is a recognized risk factor for carcinogenesis, including carcinogenesis of the prostate (1–3). Important examples of metabolic dysfunction include hyperinsulinemia and insulin resistance (1, 2). These clinical characteristics are of particular interest be- Authors' Affiliations: 1 Division of Public Health Sciences, Fred Hutchinson Cancer Research Center; 2 Department of Epidemiology, School of Public Health, University o f Washingt on , Seatt le, Washington; 3Department of Clinical Cancer Prevention, The University of Texas M.D. Anderson Cancer Center, Houston, Texas; 4Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; 5Division of Cancer Epidemiology and Genetics and 6Prostate and Urologic Cancer Research Group, Division of Cancer Prevention, National Cancer Institute, NIH, Bethesda, Maryland; and 7Departments of Medicine and Oncology, McGill University, Montreal, Canada Corresponding Author: Marian L. Neuhouser, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, M4-B402, Seattle, WA 98109-1024. Phone: 206-6674797; Fax: 206-667-7850; E-mail: [email protected]. doi: 10.1158/1940-6207.CAPR-09-0188 ©2010 American Association for Cancer Research. cause insulin-activated signaling involves pathways known to be involved in carcinogenesis (4–7). Several biologically plausible mechanisms may underlie the role of insulin in carcinogenesis. For example, insulin promotes cell division; thus, a metabolic milieu of hypersinsulinemia is likely to promote cellular proliferation and hyperplasia (8–10). Alternatively, insulin may facilitate carcinogenesis by favoring cell survival and inhibiting apoptosis through effects on AKT and mTOR (11, 12), allowing accumulation of genetic damage. Increasing evidence suggests that obesity is a strong risk factor and/or adverse prognostic factor for cancer, including prostate cancer (13, 14). Whereas the mechanism for the obesity-prostate cancer association is not definitively identified, one possibility is that obesity-related hyperinsulinemia could lead to inappropriate survival and proliferation of insulin-receptor–positive at-risk and/or transformed prostate epithelial cells (8, 10, 15–17). Consistent with this view, plasma levels of C-peptide, which serve as a marker of insulin secretion, increase with obesity (8, 18, 19), and higher levels are associated with increased risk of prostate cancer–specific mortality (7). Other evidence suggests that insulin may influence cancer risk through effects www.aacrjournals.org Downloaded from cancerpreventionresearch.aacrjournals.org on May 3, 2017. © 2010 American Association for Cancer Research. 279 Published OnlineFirst February 23, 2010; DOI: 10.1158/1940-6207.CAPR-09-0188 Neuhouser et al. on inflammation, oxidative stress, or sex hormones (5). Regardless of the mechanism, targeting the insulin axis for cancer prevention is attractive because insulin axis components are modifiable by diet, weight loss, physical activity, and pharmacologic approaches (20–22). Biomarkers of metabolic dysfunction and insulin resistance include glucose, insulin, C-peptide, glycosylated hemoglobin, and calculated measures such as homeostasis model of assessment (23). Of these, C-peptide has been used as the biomarker of insulin secretion in many population-based studies (7). Proinsulin is synthesized by the pancreas and cleaved into insulin and C-peptide before release in the circulation. In nonfasting samples, C-peptide is considered a more reliable marker of insulin secretion because, compared with insulin, it has a longer half-life and is metabolically stable (7, 24). Three investigations have examined these biomarkers (excess glucose, insulin, and insulin resistance) in relation to risk of breast and colorectal cancers (25–27), but relatively few studies have investigated insulin resistance or Cpeptide with prostate cancer risk. A Swedish cohort study reported an inverse association of high versus low plasma C-peptide with overall prostate cancer risk. However, a nonsignificant increased risk of aggressive disease [defined as Gleason ≥8, lymph node metastasis, prostate-specific antigen (PSA) >50, bone metastasis, or prostate cancer death] was observed in the cohort (28). More recently, the Physicians' Health Study showed that men diagnosed with prostate cancer who had higher versus lower baseline C-peptide had a >2-fold risk of dying from their prostate cancer. These results became somewhat attenuated after controlling for body mass index (BMI) and clinical characteristics such as Gleason grade and stage (7). Further subgroup analysis revealed that overweight men who also had elevated C-peptide had a 4-fold increased risk of death from prostate cancer (7). A recent nested case-control study (n = 100 prostate cancer cases/400 controls) reported an odds ratio (OR) of 2.55 [95% confidence interval (95% CI), 1.18-5.51; Ptrend = 0.02] for the fourth versus first quartile of serum insulin (29). In contrast, a multiethnic study of 114 prostate cancer cases and 484 controls reported no association of prediagnostic C-peptide with prostate cancer risk (30). An alternative and equally plausible pathway by which obesity may increase prostate cancer risk is via adipokines. Adipose tissue synthesizes adipokines (such as leptin and adiponectin), and the more adipose tissue the greater the synthesis of these peptides (31, 32). Leptin was originally identified as a satiety signal, but other functions were subsequently identified, including involvement in glucose and fatty acid oxidation, complex orchestrating of the hormonal control of food intake, regulation of other hormones (i.e., growth hormones and reproductive hormones), and a role in the promotion of mitogenic activity (31, 32). In addition, in vitro studies have suggested that leptin inhibits apoptosis and promotes cell proliferation in prostate cancer cells (33–35), rendering it a potential mediator of the relationship between obesity and cancer risk. 280 Cancer Prev Res; 3(3) March 2010 Finding effective measures for prostate cancer prevention is an important clinical and public health priority, particularly for high-grade disease that typically has a poor prognosis. Therefore, we sought to better understand both of these potential mechanisms (insulin secretion/insulin resistance and leptin) in relation to prostate cancer risk in the Prostate Cancer Prevention Trial (PCPT). Materials and Methods Study design and study population The PCPT was a randomized, placebo-controlled trial testing whether the 5α-reductase inhibitor finasteride could reduce the 7-y period prevalence of prostate cancer. Details regarding study design and participant characteristics have been described previously (36). Briefly, at 221 clinical centers across the United States, 18,880 men, ages 55 y and older and with a normal digital rectal exam and prostate-specific antigen (PSA) level <3.0 ng/mL, as well as no history of prostate cancer, severe benign prostatic hyperplasia, or clinically significant comorbid conditions that would have precluded successful completion of the study protocol, were randomized to receive finasteride (5 mg/d) or placebo. During the course of the PCPT, men underwent annual digital rectal exam and PSA measures and a prostate biopsy was recommended for all men with an abnormal digital rectal exam or a finasteride-adjusted PSA of ≥4.0 ng/mL (37). At the final study visit, all men without a previous diagnosis of prostate cancer were offered an end-of-study biopsy. Biopsies were collected under transrectal ultrasonographic guidance, and a minimum of six biopsy specimens (cores) were collected from each participant. All biopsies were reviewed by a local study pathologist and by a central study pathologist (38, 39). Discordant pathology interpretations were arbitrated by a referee pathologist and concordance was achieved in all cases (36, 38, 39). Pathologists were blinded to the randomization arm of all participants. Tumors were graded with the Gleason system by central pathology review at the Prostate Diagnostic Laboratory (Denver, CO). Lowgrade prostate cancer included tumors with Gleason score <7 and high-grade tumors were those with Gleason score ≥7 (36). Study procedures were approved by the Institutional Review Boards of the participating clinical centers, the Southwest Oncology Group (San Antonio, TX) and the Southwest Oncology Group Data and Statistical Center (Fred Hutchinson Cancer Research Center, Seattle, WA). All men signed informed consent. An independent data safety and monitoring committee met every 6 mo throughout the course of the trial to review data on safety, adherence, and diagnosis of prostate cancer (36). This report presents data from a nested-case control study in the PCPT. Cases were men with biopsy-determined prostate cancer identified either during an interim or end-of-study biopsy and who had baseline serum available for analysis (n = 1,803). We retained the low-grade and high-grade classifications as used in the original trial report for these analyses (low grade, Gleason <7; high Cancer Prevention Research Downloaded from cancerpreventionresearch.aacrjournals.org on May 3, 2017. © 2010 American Association for Cancer Research. Published OnlineFirst February 23, 2010; DOI: 10.1158/1940-6207.CAPR-09-0188 Finasteride, C-Peptide, and Prostate Cancer Risk grade, Gleason ≥7; ref. 36). Controls were selected from men who completed the end-of-study biopsy procedure, had no evidence of prostate cancer, and had archived baseline serum samples (n = 1,797). Controls were frequency matched to cases on distributions of age (in 5-y age groups), PCPT treatment arm (finasteride versus placebo), and positive family history for first-degree relative with prostate cancer; controls were oversampled to include all non-whites. Data collection Blood collection and processing. Nonfasting blood specimens were collected at screening (∼3 mo before randomization) and yearly thereafter. Venous blood was drawn into collection tubes without anticoagulant, refrigerated, and shipped via overnight courier to the PCPT specimen repository where they were centrifuged, aliquoted, and stored at −70°C until analysis (40). Laboratory analysis Serum C-peptide and leptin concentrations were assayed with a standard ELISA using a single production lot of reagents (Diagnostic Systems Limited). All assays were conducted in duplicate and the means of the duplicate measures were reported. Two sets of QC samples (from pooled specimens) were included for quality control and the coefficients of variation from these QC pools were 5.6% and 3.8% for the C-peptide assays and 4.9% and 4.5% for the leptin assays. Laboratory technicians were blinded to the randomization assignment and casecontrol status of all participants. Other data Demographic, personal medical history, family history of prostate cancer, and lifestyle habits such as smoking, alcohol, and physical activity were collected by self-report at baseline; the measurement characteristics of many of these self-assessment tools are published (41–43). Height and weight were assessed at the baseline clinic visit using a standard protocol (44) and weight was assessed annually thereafter. BMI was calculated as weight (kg)/[height (m)]2 and standard clinical cutoff points categorized BMI as normal (BMI <25.0), overweight (BMI 25.0 to <30.0), and obese (BMI ≥30.0; ref. 45). Circumferences of the abdomen, waist, hip, and thigh were measured at 1 y post-randomization (46). As the body circumference measurements were voluntary, some clinical centers did not participate, resulting in missing data for n = 348 (10%) of the participants. Statistical analysis The control group was oversampled with minorities to include all control-eligible non-whites. Thus, baseline demographic and lifestyle characteristics were adjusted for race (white versus non-white) using linear regression to calculate least squares means for continuous variables and adjusted percents for categorical variables. www.aacrjournals.org Serum concentrations of C-peptide and leptin were categorized into quartiles based on the distribution in the controls. Logistic regression was used to calculate ORs and 95% CIs for risk of total prostate cancer, and polytomous logistic regression was used to calculate ORs and 95% CIs of both low-grade and high-grade prostate cancers. The polytomous regression with a generalized logit link permits a model including both low-grade and high-grade cancers as outcomes in the same model, contrasted with no cancer. Model covariates were carefully selected based on a priori information about potential confounding as well as diagnostic procedures completed as part of our modeling exercises. Final covariates included age, race (white/non-white), family history of first-degree relative with prostate cancer, insulin use at baseline, BMI, and smoking (pack-years of smoking). Because this nested case-control study was part of a randomized, controlled trial, we had an a priori hypothesis that there may be effect modification of the active agent in the trial, finasteride, on C-peptide or leptin in relation to prostate cancer risk. We also hypothesized that there could be effect modification by measures of adiposity (e.g., BMI and waist circumference). Tests for multiplicative interaction were conducted by entering cross-product terms of C-peptide and finasteride or measures of adiposity and testing these terms with the Wald test. We conducted a mediating factors analysis with BMI and leptin to determine whether any observed BMI-prostate cancer risk associations were explained by leptin. All statistical tests were two-sided, with P < 0.05 considered statistically significant. SAS (version 9.0) was used for all statistical analyses. Results Cases and controls did not differ with respect to race-adjusted BMI, age, body circumferences, family history of prostate cancer, current smoking status, or alcohol habits. Controls reported higher levels of physical activity than cases (10.6% versus 8.2% were very active, P = 0.02). Controls also had more total pack-years of smoking (P = 0.02) and were more likely to report a diagnosis of diabetes or use insulin and other diabetes medications at baseline compared with cases (P = 0.05; Table 1). Unadjusted baseline serum C-peptide concentrations did not differ between cases and controls (Table 2). To determine whether finasteride influenced serum C-peptide, we assayed the blood specimens of a random subset of participants (n = 267) at both baseline and 2 years later. Whereas mean and median concentrations of C-peptide increased for all men between baseline and year 2, there was no evidence that finasteride differentially affected these changes. Mean and median baseline-year 2 differences did not vary by treatment arm, even after adjustment for years since baseline blood draw and participant weight change from baseline to year 2 (data not shown). Our initial modeling included the combined arms of the trial [intervention (finasteride) and placebo] and the interaction term between treatment arm and C-peptide. Cancer Prev Res; 3(3) March 2010 Downloaded from cancerpreventionresearch.aacrjournals.org on May 3, 2017. © 2010 American Association for Cancer Research. 281 Published OnlineFirst February 23, 2010; DOI: 10.1158/1940-6207.CAPR-09-0188 Neuhouser et al. Table 1. Race-adjusted baseline demographic and lifestyle characteristics of the PCPT participants (n = 3,600) P* Prostate cancer Cases (n = 1,803) Controls (n = 1,797) n (%) n (%) 1,674 (92.8) 82 (4.5) 47 (2.6) 1,426 (79.4) 174 (9.7) 197 (11.0) LS mean† (95% CI) LS mean (95% CI) 63.6 27.5 101.8 0.96 14.0 9.7 63.7 (63.4-63.9) 27.6 (27.4-27.8) 102.3 (101.8-102.8) 0.96 (0.96-0.96) 15.3 (14.6-16.1) 9.2 (8.5-9.9) Race White Black Other Age (y) BMI (kg/m2) Waist circumference (cm) Waist-hip ratio Smoking (pack-years) Alcohol intake (g/d) (63.3-63.8) (27.3-27.7) (101.3-102.3) (0.95-0.96) (13.2-14.8) (9.0-10.4) n (%), adjusted† Intervention arm‡ Diabetes or insulin use Family history of prostate cancer BMI (kg/m2) Normal (<25.0) Overweight (25.0-29.9) Obese (≥30.0) Physical activity Sedentary Light activity Moderate activity Very active Smoking status Never smoker Current smoker Past smoker Education High school or less Some college/college degree Graduate/professional school 0.58 0.42 0.16 0.70 0.02 0.28 n (%), adjusted 761 (43.0) 84 (5.3) 384 (20.8) 763 (41.7) 133 (6.8) 382 (21.8) 0.42 0.05 0.48 498 (27.7) 913 (50.8) 376 (21.3) 447 (25.3) 941 (53.2) 391 (21.3) 0.11 0.15 0.99 309 746 592 149 313 738 550 188 (17.1) (41.5) (30.8) (10.6) 0.68 0.91 0.20 0.02 644 (35.4) 122 (7.1) 1,037 (57.5) 615 (34.6) 138 (7.3) 1,044 (58.1) 0.62 0.87 0.69 308 (17.6) 490 (27.7) 1,004 (54.7) 348 (18.9) 542 (29.7) 906 (51.4) 0.32 0.20 0.05 (17.6) (41.3) (32.9) (8.2) *P values are adjusted for race using linear regression to calculate least squares means, adjusted percents, and P values (see Materials and Methods for details). † Least squares means and adjusted percents are adjusted for race (white vs non-white) due to the inclusion of all non-whites in the control group (see Materials and Methods for details). ‡ Intervention arm participants were randomized to finasteride. Notably, we observed a statistically significant interaction of C-peptide with treatment arm (Pinteraction = 0.04 for all cancers and P = 0.03 for Gleason ≥7). Therefore, all remaining models were stratified by treatment arm. Additionally, because men with self-reported diabetes at baseline might have higher circulating C-peptide due to 282 Cancer Prev Res; 3(3) March 2010 disease-associated poor glycemic control, we conducted additional analyses excluding diabetic men to determine whether they were driving the observed associations. However, because these analyses did not materially alter the results or their interpretation, men with diabetes at baseline were retained in the final model. Cancer Prevention Research Downloaded from cancerpreventionresearch.aacrjournals.org on May 3, 2017. © 2010 American Association for Cancer Research. Published OnlineFirst February 23, 2010; DOI: 10.1158/1940-6207.CAPR-09-0188 Finasteride, C-Peptide, and Prostate Cancer Risk Table 3 gives the results for multivariate-adjusted associations of serum C-peptide with prostate cancer risk, stratified by treatment arm. In the placebo arm, C-peptide was associated with modest increases in risk for total and low-grade disease (OR, 1.21; 95% CI, 0.93-1.57; Ptrend = 0.11 for all cancers). Findings for high-grade disease were considerably stronger. For men in the placebo arm, those with higher baseline serum C-peptide concentrations had a nearly 2-fold, statistically significant increased risk of high-grade prostate cancer, compared with men with lower baseline serum C-peptide (OR, 1.88; 95% CI, 1.19-2.97; Ptrend = 0.004). Whereas the PCPT defined high-grade as Gleason ≥7, analyses where high grade was restricted to Gleason ≥8 were equally strong, but cell sizes were very small and confidence intervals very wide. Therefore, data presented are for Gleason scores <7 and ≥7 only. We next examined C-peptide as a continuous variable. In analyses where C-peptide was modeled as log(C-peptide), associations with high-grade disease were strong. For every unit increase in log(C-peptide), men randomized to placebo had a 39% increased risk of high-grade prostate cancer (P < 0.01). In contrast to the C-peptide risk associations observed in the placebo arm, among men randomized to finasteride, there was no evidence for C-peptide–associated risk with total prostate cancer or low-grade or high grade-disease, even for men with high serum C-peptide. For lowgrade disease, there was a suggestion of lowered risk among finasteride users (OR for high versus low C-peptide, 0.77; 95% CI, 0.54-1.09). However, for high-grade disease, prostate cancer risk estimates hovered around unity. Results were similar when high grade was defined as Gleason ≥8. Likewise, when C-peptide was modeled as a continuous variable, there was a modest suggestion of lowered risk for low-grade disease; for each unit increase of log(C-peptide), the OR for prostate cancer was 0.87 (95% CI, 0.72-1.05; Ptrend = 0.16). In the continuous model, no association was observed between C-peptide and high-grade prostate cancer for men taking finasteride. All results in Table 3 were repeated, restricting the sample to men who were black or non-Hispanic white (i.e., excluding all other race groups). The results and their interpretation did not differ from models where all race/ethnicities were included. We also found no differences in risk across race groups, albeit sample sizes were small (data not shown). Therefore, the final models as presented included all non-white and white men. Adiposity strongly influences insulin resistance and Cpeptide. In this study sample, the correlations of BMI and waist circumference with serum C-peptide were r = 0.25 and r = 0.27, respectively. To investigate whether these adiposity measures modified the association between C-peptide and prostate cancer risk, we modeled Cpeptide with the following interaction terms in separate models: (a) BMI 25.0-29.9 (overweight), BMI ≥30.0 (obese); (b) elevated waist circumference (≥102 cm); (c) elevated waist-hip ratio (≥1.0); and (d) a category termed “very high risk of metabolic dysfunction” defined as BMI ≥30.0 + waist circumference ≥102 cm, or BMI ≥35.0 (45). We restricted these analyses to the placebo arm and we presented high-grade disease only because this was the group with the elevated risk in the Table 3 models. The results presented in Table 4 were for low and high C-peptide (above and below the median concentration), Table 2. Distributions of C-peptide in the PCPT Baseline serum C-peptide (ng/mL) All participants Cases Controls n Mean SD 25th percentile 50th percentile 75 percentile 3,600 1,803 1,797 3.64 3.64 3.63 2.32 2.32 2.33 1.86 1.87 1.84 3.08 3.14 3.03 4.88 4.87 4.90 Baseline and year 2 serum C-peptide (ng/mL)* All participants* Cases All cases Placebo Finasteride Controls All controls Placebo Finasteride n Baseline median Baseline mean SD Year 2 median Year 2 mean SD 267 3.08 3.56 2.18 4.06 4.46 2.71 127 67 60 3.32 3.21 3.91 3.84 3.60 4.10 2.25 2.05 2.45 4.32 4.27 4.52 4.78 4.46 5.13 2.77 2.64 2.89 140 73 67 2.78 2.76 2.89 3.32 3.23 3.41 2.08 2.05 2.13 3.58 3.81 3.11 4.14 4.24 4.03 2.62 2.46 2.80 *Subset of randomly selected participants (n = 267) had repeat measures. www.aacrjournals.org Cancer Prev Res; 3(3) March 2010 Downloaded from cancerpreventionresearch.aacrjournals.org on May 3, 2017. © 2010 American Association for Cancer Research. 283 Published OnlineFirst February 23, 2010; DOI: 10.1158/1940-6207.CAPR-09-0188 Neuhouser et al. Table 3. Associations of serum C-peptide concentrations with prostate cancer risk in the PCPT by treatment arm (placebo/finasteride) Placebo arm All cases No. cases ORmultivariable Gleason <7† No. cases ORmultivariable Gleason 7-10† No. cases ORmultivariable Quartile of serum C-peptide concentration (ng/mL) <1.84 1.85-3.03 3.04-4.90 ≥4.91 Ptrend (95% CI) 239 1.0 266 1.25 (0.98-1.61) 280 1.37 (1.07-1.76) 247 1.21 (0.93-1.57) 0.11 adjusted* (95% CI) 191 1.00 209 1.26 (0.96-1.64) 205 1.29 (0.99-1.69) 171 1.09 (0.82-1.45) 0.49 adjusted* (95% CI) 35 1.00 49 1.51 (0.95-2.42) 63 1.95 (1.24-3.07) 65 1.88 (1.19-2.97) 0.004 adjusted* Continuous model‡ Gleason <7 Gleason 7-10 Finasteride arm All cases No. cases ORmultivariable Gleason <7† No. cases ORmultivariable Gleason 7-10† No. cases ORmultivariable OR (95% CI) P 1.06 (0.91-1.23) 1.39 (1.09-1.76) 0.44 0.01 Quartile of serum C-peptide concentration (ng/mL) <1.84 1.85-3.03 3.04-4.90 ≥4.91 Ptrend (95% CI) 193 1.0 165 0.72 (0.53-0.98) 203 0.84 (0.63-1.14) 194 0.86 (0.63-1.17) 0.55 adjusted* (95% CI) 126 1.00 89 0.61 (0.43-0.87) 126 0.84 (0.60-1.17) 107 0.77 (0.54-1.09) 0.39 adjusted* (95% CI) 60 1.00 63 0.87 (0.57-1.32) 70 0.90 (0.59-1.36) 81 1.07 (0.71-1.62) 0.67 adjusted* Continuous model‡ Gleason <7 Gleason 7-10 OR (95% CI) P 0.87 (0.72-1.05) 0.96 (0.76-1.20) 0.16 0.69 *ORs are adjusted for age, race (white/non-white), family history of prostate cancer, insulin use at baseline, BMI (kg/m2), and smoking (pack-years). † The ORs for prostate cancer risk using both low-grade and high-grade disease (Gleason <7 and Gleason 7-10) as outcomes in the same model were calculated using polytomous logistic regression with generalized logit link.; model includes both low-grade (Gleason <7) and high-grade (Gleason 7-10), contrasted with no cancer. ‡ For the continuous models, the ORs represent the change in risk for each unit increase in log(C-peptide). and for each model the reference group is the lowest risk category (i.e., low C-peptide + normal BMI, or low C-peptide + waist-hip ratio <1.0). We observed no evidence for effect modification of C-peptide by measures of adiposity. 284 Cancer Prev Res; 3(3) March 2010 We conducted several other exploratory analyses in an attempt to further understand why the C-peptide/high-grade disease association was observed only in the PCPT placebo arm. First, we examined whether results may have been biased by the fact that PCPT participants had end-of-study Cancer Prevention Research Downloaded from cancerpreventionresearch.aacrjournals.org on May 3, 2017. © 2010 American Association for Cancer Research. Published OnlineFirst February 23, 2010; DOI: 10.1158/1940-6207.CAPR-09-0188 Finasteride, C-Peptide, and Prostate Cancer Risk grade disease in the placebo arm (but not finasteride arm) even after controlling for leptin (OR, 1.99; 95% CI, 1.243.19; Ptrend < 0.001; data not shown). The association of obesity with high-grade prostate cancer risk does not seem to be mediated by leptin. biopsies in addition to biopsies by indication throughout the trial. However, analyses stratified by end-of-study versus for-cause biopsy and analyses stratified by year of diagnosis did not change the interpretation of results. Similarly, neither adjusting for time since blood draw, prostate volume, trends in PSA nor changes in participant weight over time altered the results or their interpretation (data not shown). To fully understand the associations of obesity-related factors with prostate cancer risk, particularly high-grade disease, we next investigated whether serum leptin was associated with prostate cancer risk (Table 5). Specifically, we conducted a mediating factors analysis to understand whether leptin mediates the association of obesity with prostate cancer risk, as suggested by in vitro studies (33, 35). Our initial modeling did not show an interaction of finasteride with leptin, and thus for these models, the intervention and placebo arms are combined. When BMI is modeled as the primary exposure, the OR for high-grade prostate cancer among obese men is 1.39 (95% CI, 1.031.87; Ptrend = 0.03). Obesity was associated with a modest inverse association with low-grade disease (OR, 0.80; 95% CI, 0.64-1.0; Ptrend = 0.04). Leptin alone was likewise inversely associated with low-grade, but not high-grade, prostate cancer. In the mediating factors analysis, the BMI association with high-grade disease remains strong, even after including leptin in the model. Finally, we reran the C-peptide models again (from Table 3) but controlling for leptin. C-peptide continued to be associated with high- Discussion In the PCPT, men in the placebo arm of the trial who had higher serum C-peptide had a nearly 2-fold increased risk of high-grade prostate cancer, relative to men with lower serum C-peptide. The results suggest that metabolic abnormalities are associated with prostate cancer risk, but the mechanism seems to be through insulin resistance and not via adipokines, such as leptin. The C-peptide findings were independent of the principal risk factors for prostate cancer: age, race, and family history of prostate cancer (47). The observed associations were also independent of adiposity measures, such as BMI and waist circumference, which recent reports suggest are important prostate cancer risk factors (14, 48, 49). For every unit increase in log(C-peptide), there was a 39% increased risk of highgrade prostate cancer. These findings are strengthened by the fact that all men underwent either interim (cases only) or end-of-study (cases and controls) biopsies in the PCPT (36). Thus, the control group is not contaminated with any preclinical cases, as may be the case with other studies. In contrast, men taking finasteride had no apparent increased risk for high-grade prostate cancer, even for Table 4. Adiposity/C-peptide interactions in relation to high-grade prostate cancer in the PCPT (placebo arm only) Adiposity measures BMI Normal (BMI <25 × C-peptide) Overweight (BMI 25.0-29.9 × C-peptide) Obese (BMI ≥30.0 × C-peptide) Waist circumference Waist <102 cm × C-peptide Waist ≥102 cm × C-peptide Waist-hip ratio Waist-hip <1.0 × C-peptide Waist-hip ≥1.0 × C-peptide Very high risk‡ Low risk × C-peptide Very high risk × C-peptide Total n C-peptide <3.08 ng/mL* C-peptide ≥3.08 ng/mL* Cases (n) OR† (95% CI) Cases (n) OR† (95% CI) 49 106 57 25 41 19 1.0 (reference) 0.80 (0.47-1.36) 1.62 (0.84-3.15) 24 65 38 1.43 (0.77-2.66) 1.40 (0.66-2.96) 0.72 (0.30-1.72) 92 104 45 34 1.0 (reference) 0.98 (0.58-1.66) 47 70 1.50 (0.95-2.38) 1.03 (0.54-1.97) 160 36 69 10 1.0 (reference) 0.73 (0.35-1.49) 91 26 1.56 (1.09-2.23) 0.98 (0.41-2.33) 145 46 63 15 1.0 (reference) 1.20 (0.57-2.54) 82 31 1.71 (1.19-2.47) 0.59 (0.27-1.28) NOTE: Polytomous regression was used in the analysis but only high-grade results are shown in the table. *Median serum C-peptide concentration = 3.08 ng/mL. † All ORs are adjusted for age (continuous), race (white vs nonwhite), family history of prostate cancer, insulin use at baseline, BMI continuous (except the model with BMI interactions), and pack-years of cigarettes smoked (continuous). P values for all interaction tests are >0.10. ‡ Very high risk is defined as BMI ≥30 + waist circumference ≥102 cm, or BMI ≥35 (see text for details). www.aacrjournals.org Cancer Prev Res; 3(3) March 2010 Downloaded from cancerpreventionresearch.aacrjournals.org on May 3, 2017. © 2010 American Association for Cancer Research. 285 Published OnlineFirst February 23, 2010; DOI: 10.1158/1940-6207.CAPR-09-0188 Neuhouser et al. Table 5. Associations of leptin with low-grade and high-grade prostate cancers in the PCPT (n = 3,565) Gleason ≥7 (n = 486) Gleason <7 (n = 1,224) Model BMI† alone Normal (<25.0) Overweight (25.0-29.0) Obese (≥30.0) Leptin alone Q1 (<5.2 ng/mL)§ Q2 (5.2-8.6 ng/mL) Q3 (8.6-13.3 ng/mL) Q4 (>13.3 ng/mL) BMI and leptin Normal (<25.0) Overweight (25.0-29.0) Obese (≥30.0) Q1 leptin§ Q2 leptin Q3 leptin Q4 leptin OR* (95% CI) Ptrend OR* (95% CI) Ptrend 1.0 (reference) 0.83 (0.70-0.99) 0.80 (0.64-1.00) 0.04 1.0 (reference) 1.04 (0.81-1.33) 1.39 (1.03-1.87) 0.03 1.0 0.94 0.88 0.72 (reference) (0.77-1.16) (0.71-1.08) (0.58-0.90) 0.003 1.0 1.22 1.06 1.18 (reference) (0.92-1.62) (0.79-1.43) (0.88-1.57) 0.48 1.0 0.88 0.96 1.0 0.98 0.92 0.75 (reference) (0.73-1.07) (0.73-1.26) (reference) (0.79-1.21) (0.73-1.16) (0.58-0.98) 0.62 1.0 1.03 1.46 1.0 1.18 0.98 0.98 (reference) (0.78-1.37) (1.01-2.10) (reference) (0.87-1.60) (0.70-1.36) (0.68-1.40) 0.05 0.04 0.65 NOTE: n = 3,565 PCPT participants, includes 1,787 cases and 1,778 controls; Gleason score not available for all men. *ORs are adjusted for age, race (white/non-white), family history of prostate cancer, treatment arm (finasteride or placebo), pack years of cigarette smoking, and baseline insulin use. † BMI = weight (kg)/[height (m)]2. § Quartiles of leptin are based on the distribution in the controls. men with high serum C-peptide. The strength of the interaction of C-peptide with finasteride was somewhat unexpected. Finasteride inhibits 5α-reductase, which converts testosterone to the more potent and biologically active dihydrotestosterone (36, 50). We do not have evidence that finasteride affects C-peptide per se because analysis of the small subset (n = 267) of specimens assayed for both baseline and year 2 serum C-peptide did not support a C-peptide–reducing effect by finasteride. There is some evidence, however, that finasteride may indirectly affect metabolic function. Two previous reports showed that finasteride slows weight gain trajectories (51, 52). If the finasteride-induced decreased weight gain slope affected some of the downstream events that are upregulated by C-peptide (e.g., AKT and mTOR; refs. 12, 17), then finasteride could essentially override C-peptide–driven events without affecting C-peptide itself. Another possible explanation is that proliferation of neoplastic cells in the prostate may depend on both insulin and androgens. Because androgen levels (such as dihydrotestosterone) are reduced among men on finasteride, neoplastic progression could be slowed despite high insulin levels. It is also possible that multiple mechanisms are at work. Investigations using methods developed for genetic epidemiology that simultaneously model metabolic and hormonal pathways, as well as the role of finasteride in those pathways, may 286 Cancer Prev Res; 3(3) March 2010 be a particularly useful approach to use in the future to understand these complex relationships (53–55). Regardless of the underlying biological mechanism, the evidence that men with higher serum C-peptide who used finasteride, but did not have an increased prostate cancer risk, may be clinically meaningful and should be investigated further. The results from the PCPT placebo arm are consistent with most, but not all, previous studies of C-peptide and prostate cancer risk. The Physicians' Health Study reported that risk of death from prostate cancer was >2-fold higher for men with higher versus lower C-peptide (7). Unlike the PCPT, however, the Physicians' Health Study observed an interaction of BMI with C-peptide such that men in the highest C-peptide quartile who were also overweight (BMI >25.0) had a 4-fold increased risk of prostate cancer mortality, but those with high C-peptide who were not overweight had no increased risk of prostate cancer death (7). It is possible that the PCPT did not have sufficient variation in adiposity measures to detect an interaction effect with C-peptide because only 25% of the study sample was of normal BMI. Other studies have reported on insulin and insulin resistance measures such as homeostasis model of assessment. Two studies conducted in Chinese men support a positive association of insulin or insulin resistance with prostate cancer risk (5, 6), as does one recent Cancer Prevention Research Downloaded from cancerpreventionresearch.aacrjournals.org on May 3, 2017. © 2010 American Association for Cancer Research. Published OnlineFirst February 23, 2010; DOI: 10.1158/1940-6207.CAPR-09-0188 Finasteride, C-Peptide, and Prostate Cancer Risk study of Finnish men (29). In contrast to the positive reports for C-peptide and other measures of metabolic dysfunction, Borugian et al. (30) reported no association of serum C-peptide with prostate cancer risk, but the study was very small (n = 57 cases) and no results were reported by disease stage or Gleason grade. Despite the increasing evidence in this and other reports that metabolic dysfunction increases prostate cancer risk (5, 7, 13, 48), one somewhat paradoxical observation still exists. Several observational studies have reported inverse associations of diabetes with prostate cancer risk (14, 56, 57). Because diabetes is a disease of disordered glucose metabolism, and often the consequence of obesity (18, 58), evidence suggesting that diabetes reduces prostate cancer risk is curious. Diabetic men also have altered sex hormone profiles as a consequence of their disease (59), which could possibly explain the relationship, but how these complex pathways weave together to affect disease risk is yet to be determined. A particularly complex piece of this clinical picture is the marked heterogeneity of diabetes. For example, many patients with type II diabetes initially have hyperinsulinemia, but in later stages of the disease actually have hypoinsulinemia, a state that may further reduce androgens and potentially reduce prostate cancer risk (14, 60). Alternatively, the link between diabetes and decreased prostate cancer risk may relate to drugs used to treat diabetes rather than diabetes itself. Metformin is very commonly used in the treatment of type II diabetes (61), and metformin has recently been shown to have potent antiproliferative properties (62). These may relate not only to metformin-induced reduction in the hyperinsulinemia seen in type II diabetics but also to direct mechanisms of growth inhibition related to metformin activation of the AMP kinase signaling pathway (63–66). In addition, many diabetics routinely use statins due to comorbid cardiovascular symptoms; statins have been noted to lower prostate cancer risk (67, 68). Future studies, rather than simply examining relationships between diabetes and prostate cancer, may provide more insight into mechanisms by exploring individually the specific relationships between risk and the levels of various hormones (including insulin), glucose, measures of obesity, and antidiabetic drug use. Although not definitive, several recent studies have raised the question of increased cancer risk among diabetics who use insulin, in contrast to possibly reduced risk among those who use metformin (69, 70). Our finding of no relationship of leptin to high-grade prostate cancer risk is a potentially important one, particularly with regard to formulating programs for prevention and control. Evidence to support an association of leptin with prostate cancer is inconsistent from observational studies. A Swedish case-control study reported a relative risk of 2.4 for high versus low serum leptin in relation to prostate cancer risk (71). However, two subsequent case-control studies in China and Norway reported no statistically significant association of leptin with prostate cancer (6, 72). A more recent case-control study in Texas also www.aacrjournals.org reported no association of leptin with prostate cancer risk (73). However, the PCPT results presented here are consistent with results from a study using the fatless A-ZIP/F-1 transgenic mouse model. These animals are insulin resistant and are in a chronic state of inflammation, but they lack white adipose tissue and thus have near undetectable levels of adipokines, such as leptin (74, 75). Nunuz et al. reported that the A-ZIP/F-1 mice produced more skin and mammary tumors than wild-type mice [using a classic topical 7,12-dimethylbenz(a)anthracene application for the skin cancers and breeding with C3(1)/T-Ag transgenic mice for the mammary cancers]. The tumors developed in spite of very low levels of adipokines but high levels of insulin and inflammatory factors and upregulation of insulin-regulated signaling pathways involved in carcinogenesis. The authors and others conclude that the obesitycancer association may be mediated by insulin resistance and inflammation, rather than adipokines (74, 75). Our results in the PCPT are similar; C-peptide was strongly associated with increased risk of prostate cancer and the effects remained strong after controlling for obesity-related factors. The relationships were attenuated by finasteride. Conversely, the association of obesity with prostate cancer risk was not mediated by leptin. Such findings quite likely have relevance for future programs of prostate cancer prevention and control wherein it might be most effective to improve measures of insulin sensitivity as a measure of prevention and control. This study has several strengths. The PCPT was a large placebo-controlled randomized trial. The trial design specified that prostate cancer outcomes would be based on biopsy results. As such, the control group used in these analyses all had negative prostate biopsies, largely eliminating the possibility that controls may have had undiagnosed or undetected disease. Other strengths include carefully collected data throughout the course of the trial and a central pathology laboratory for uniform adjudication of all cases (including adjudication of Gleason grade). Limitations should also be noted, including the fact that the PCPT included few minorities. Although we oversampled non-white controls to increase power for analyses by race, the power for any race-specific subgroups was limited. Further, few deaths from prostate cancer have occurred in the PCPT and thus we were unable to conduct analyses to examine mortality as an end point. In conclusion, these results from the PCPT suggest that men with elevated C-peptide have an increased risk of high-grade prostate cancer. The lack of support in the PCPT for an association of leptin with prostate cancer suggests that the obesity-cancer associations may be mediated by insulin resistance rather than by adipose-derived factors, such as leptin. The findings reported here confirm and extend results from other cohorts (7). Because insulin resistance–type syndromes respond well to lifestyle and pharmacologic treatments, consideration should be given to preventive interventions to lower insulin resistance as a means of prostate cancer prevention. Our finding that Cancer Prev Res; 3(3) March 2010 Downloaded from cancerpreventionresearch.aacrjournals.org on May 3, 2017. © 2010 American Association for Cancer Research. 287 Published OnlineFirst February 23, 2010; DOI: 10.1158/1940-6207.CAPR-09-0188 Neuhouser et al. men with elevated C-peptide who also used finasteride had no increased prostate cancer risk is novel. Further research is needed to understand the clinical significance and mechanisms underlying the finasteride/Cpeptide interaction presented in this report. We cannot rule out the possibility that C-peptide levels may be of use in defining a subpopulation of men for whom finasteride-based prevention programs would be particularly useful. Disclosure of Potential Conflicts of Interest No potential conflicts of interest were disclosed. Acknowledgments We thank the PCPT participants and clinic staff, and Drs. Scott Lippman, Ian Thompson, M. 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Cancer Prev Res; 3(3) March 2010 Downloaded from cancerpreventionresearch.aacrjournals.org on May 3, 2017. © 2010 American Association for Cancer Research. 289 Correction Correction: Finasteride Modifies the Relation between Serum C-Peptide and Prostate Cancer Risk: Results from the Prostate Cancer Prevention Trial Cancer Prevention Research In this article (Cancer Prev Res 2010;3:279–89), which was published in the March 2010 issue of Cancer Prevention Research (1), Table 4 included a mistake in the calculation of some of the odds ratios. The corrected table appears below: Table 4. Adiposity/C-peptide interactions in relation to high-grade prostate cancer in the PCPT (placebo arm only) Total n BMI Normal Overweight Obese Waist Circumference Waist <102 Waist >=102 Waist:Hip Ratio Waist:Hip <1.0 Waist:Hip >=1.0 Very High Risk Low Risk High Risk C-peptide <3.08 ng/mL C-peptide ≥3.08 ng/mL Cases (n) OR (95% CI) Cases (n) OR (95% CI) 49 106 57 25 41 19 1.0 (reference) 0.80 (0.47-1.36) 1.62 (0.84-3.15) 24 65 38 1.43 (0.77-2.66) 1.59 (0.96-2.64) 1.67 (0.95-2.91) 92 104 45 34 1.0 (reference) 0.98 (0.58-1.66) 47 70 1.50 (0.95-2.38) 1.52 (0.93-2.49) 160 36 69 10 1.0 (reference) 0.73 (0.35-1.49) 91 26 1.56 (1.09-2.23) 1.11 (0.65-1.90) 145 46 63 15 1.0 (reference) 1.20 (0.57-2.54) 82 31 1.71 (1.19-2.47) 1.21 (0.62-2.37) Reference 1. Neuhouser ML, Till C, Kristal AR, Goodman P, Hoque A, Platz EA, Hsing AW, Albanes D, Parnes HL, Pollak M. Finasteride modifies the relation between serum C-peptide and prostate cancer risk: results from the prostate cancer prevention trial. Can Prev Res 2010;3:279–89. ©2010 American Association for Cancer Research. doi: 10.1158/1940-6207.CAPR-10-0261 www.aacrjournals.org 1503 Published OnlineFirst February 23, 2010; DOI: 10.1158/1940-6207.CAPR-09-0188 Finasteride Modifies the Relation between Serum C-Peptide and Prostate Cancer Risk: Results from the Prostate Cancer Prevention Trial Marian L. Neuhouser, Cathee Till, Alan Kristal, et al. Cancer Prev Res 2010;3:279-289. Published OnlineFirst February 23, 2010. 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